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Background: Malaria transmission is measured using entomological inoculation rate (EIR), number of infective mosquito bites/person/unit time. Understanding heterogeneity of malaria transmission has been difficult due to a lack of appropriate data. A comprehensive entomological database compiled by the Malaria Transmission Intensity and Mortality Burden across Africa (MTIMBA) project (2001–2004) at several sites is the most suitable dataset for studying malaria transmission–mortality relations. The data are sparse and large, with small-scale spatial–temporal variation. Objective: This work demonstrates a rigorous approach for analysing large and highly variable entomological data for the study of malaria transmission heterogeneity, measured by EIR, within the Rufiji Demographic Surveillance System (DSS), MTIMBA project site in Tanzania. Design: Bayesian geostatistical binomial and negative binomial models with zero inflation were fitted for sporozoite rates (SRs) and mosquito density, respectively. The spatial process was approximated from a subset of locations. The models were adjusted for environmental effects, seasonality and temporal correlations and assessed based on their predictive ability. EIR was calculated using model-based predictions of SR and density. Results: Malaria transmission was mostly influenced by rain and temperature, which significantly reduces the probability of observing zero mosquitoes. High transmission was observed at the onset of heavy rains. Transmission intensity reduced significantly during Year 2 and 3, contrary to the Year 1, pronouncing high seasonality and spatial variability. The southern part of the DSS showed high transmission throughout the years. A spatial shift of transmission intensity was observed where an increase in households with very low transmission intensity and significant reduction of locations with high transmission were observed over time. Over 68 and 85% of the locations selected for validation for SR and density, respectively, were correctly predicted within 95% credible interval indicating good performance of the models. Conclusion: Methodology introduced here has the potential for efficient assessment of the contribution of malaria transmission in mortality and monitoring performance of control and intervention strategies.

Crude rates such as the crude death rate are functions of both the age-specific rates and the age composition of a population. However, differences in the age structure between two populations or two time periods can result in specious differences in the corresponding crude rates making direct comparisons between populations or across time inappropriate. Therefore, when comparing crude rates between populations, it is desirable to eliminate or minimize the influence of age composition. This task is accomplished by using a standard age structure yielding an age-standardized rate. This paper proposes an updated International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) standard for use in low- and middle-income countries (LMICs) based on newly available data from the health and demographic surveillance system site members of the INDEPTH network located throughout Africa and southern Asia. The updated INDEPTH standard should better reflect the age structure of LMICs and result in more accurate health indicators and demographic rates. We demonstrate use of the new INDEPTH standard along with several existing ‘world’ standards and show how resulting age-standardized crude deaths rates differ when using the various standard age compositions.

Background: Globally, ageing impacts all countries, with a majority of older persons residing in lower- and middle-income countries now and into the future. An understanding of the health and well-being of these ageing populations is important for policy and planning; however, research on ageing and adult health that informs policy predominantly comes from higher-income countries. A collaboration between the WHO Study on global AGEing and adult health (SAGE) and International Network for the Demographic Evaluation of Populations and Their Health in developing countries (INDEPTH), with support from the US National Institute on Aging (NIA) and the Swedish Council for Working Life and Social Research (FAS), has resulted in valuable health, disability and well-being information through a first wave of data collection in 2006–2007 from field sites in South Africa, Tanzania, Kenya, Ghana, Viet Nam, Bangladesh, Indonesia and India. Objective: To provide an overview of the demographic and health characteristics of participating countries, describe the research collaboration and introduce the first dataset and outputs. Methods: Data from two SAGE survey modules implemented in eight Health and Demographic Surveillance Systems (HDSS) were merged with core HDSS data to produce a summary dataset for the site-specific and cross-site analyses described in this supplement. Each participating HDSS site used standardised training materials and survey instruments. Face-to-face interviews were conducted. Ethical clearance was obtained from WHO and the local ethical authority for each participating HDSS site. Results: People aged 50 years and over in the eight participating countries represent over 15% of the current global older population, and is projected to reach 23% by 2030. The Asian HDSS sites have a larger proportion of burden of disease from non-communicable diseases and injuries relative to their African counterparts. A pooled sample of over 46,000 persons aged 50 and over from these eight HDSS sites was produced. The SAGE modules resulted in self-reported health, health status, functioning (from the WHO Disability Assessment Scale (WHODAS-II)) and well-being (from the WHO Quality of Life instrument (WHOQoL) variables). The HDSS databases contributed age, sex, marital status, education, socio-economic status and household size variables. Conclusion: The INDEPTH WHO–SAGE collaboration demonstrates the value and future possibilities for this type of research in informing policy and planning for a number of countries. This INDEPTH WHO–SAGE dataset will be placed in the public domain together with this open-access supplement and will be available through the GHA website (www.globalhealthaction.net) and other repositories. An improved dataset is being developed containing supplementary HDSS variables and vignette-adjusted health variables. This living collaboration is now preparing for a next wave of data collection.

Background: Declining rates of fertility and mortality are driving demographic transition in all regions of the world, leading to global population ageing and consequently changing patterns of global morbidity and mortality. Understanding sex-related health differences, recognising groups at risk of poor health and identifying determinants of poor health are therefore very important for both improving health trajectories and planning for the health needs of ageing populations. Objectives: To determine the extent to which demographic and socio-economic factors impact upon measures of health in older populations in Africa and Asia; to examine sex differences in health and further explain how these differences can be attributed to demographic and socio-economic determinants. Methods : A total of 46,269 individuals aged 50 years and over in eight Health and Demographic Surveillance System (HDSS) sites within the INDEPTH Network were studied during 2006–2007 using an abbreviated version of the WHO Study on global AGEing and adult health (SAGE) Wave I instrument. The survey data were then linked to longitudinal HDSS background information. A health score was calculated based on self-reported health derived from eight health domains. Multivariable regression and post-regression decomposition provide ways of measuring and explaining the health score gap between men and women. Results: Older men have better self-reported health than older women. Differences in household socio-economic levels, age, education levels, marital status and living arrangements explained from about 82% and 71% of the gaps in health score observed between men and women in South Africa and Kenya, respectively, to almost nothing in Bangladesh. Different health domains contributed differently to the overall health scores for men and women in each country. Conclusion: This study confirmed the existence of sex differences in self-reported health in low- and middle-income countries even after adjustments for differences in demographic and socio-economic factors. A decomposition analysis suggested that sex differences in health differed across the HDSS sites, with the greatest level of inequality found in Bangladesh. The analysis showed considerable variation in how differences in socio-demographic and economic characteristics explained the gaps in self-reported health observed between older men and women in African and Asian settings. The overall health score was a robust indicator of health, with two domains, pain and sleep/energy, contributing consistently across the HDSS sites. Further studies are warranted to understand other significant individual and contextual determinants to which these sex differences in health can be attributed. This will lay a foundation for a more evidence-based approach to resource allocation, and to developing health promotion programmes for older men and women in these settings.

Background: Increasingly, human populations throughout the world are living longer and this trend is developing in sub-Saharan Africa. In developing African countries such as Tanzania, this demographic phenomenon is taking place against a background of poverty and poor health conditions. There has been limited research on how this process of ageing impacts upon the health of older people within such low-income settings. Objective: The objective of this study is to describe the impacts of ageing on the health status, quality of life and well-being of older people in a rural population of Tanzania. Design: A short version of the WHO Survey on Adult Health and Global Ageing questionnaire was used to collect information on the health status, quality of life and well-being of older adults living in Ifakara Health and Demographic Surveillance System, Tanzania, during early 2007. Questionnaires were administered through this framework to 8,206 people aged 50 and over. Results: Among people aged 50 and over, having good quality of life and health status was significantly associated with being male, married and not being among the oldest old. Functional ability assessment was associated with age, with people reporting more difficulty in performing routine activities as age increased, particularly among women. Reports of good quality of life and well-being decreased with increasing age. Women were significantly more likely to report poor quality of life (odds ratio 1.31; p